A key aspect for the consumer when it comes to deciding on a particular product is the colour. In order to make fruit available to consumers as early as possible, the collection of oranges and mandarins begins before they ripen fully and reach their typical orange colour. As a result, they are therefore subjected to certain degreening treatments, depending on their standard colour citrus index at harvest. Recently, a mobile platform that incorporates a computer vision system capable of pre-sorting the fruit while it is being harvested has been developed as an aid in the harvesting task. However, due to the restrictions of working in the field, the computer vision system developed for this machine is limited in its technology and processing capacity compared to conventional systems. This work shows the optimised algorithms for estimating the colour of citrus in-line that were developed for this mobile platform and its performance is evaluated against that of a spectrophotometer used as a reference in the analysis of colour in food. The results obtained prove that our analysis system predicts the colour index of citrus with a good reliability (R 2 = 0.925) working in real time. Findings also show that it is effective for classifying harvested fruits in the field according to their colour.
Food and Bioprocess Technology – Springer Journals
Published: Dec 8, 2012
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